This document discusses using a graph database for analyzing Liferay data. It describes what a graph is from a data structure perspective and provides examples of why graphs are useful, such as for modeling networks, human relationships, and the human body. The document then demonstrates how graphs can be used for various Liferay use cases like discovering relationships between users, content, and entities. It also discusses how graph algorithms and staging processes that replicate data between sites can utilize graph structures and operations.

1. Amazing Title Goes Here
Awesome Subtitle
Name Name
Title Title Title Title Title
Using a graph database for analyzing
your Liferay data
Máté Thurzó @matethurzo
Staging Lead, Senior Software Engineer

2. Budapest

4. What is
graph?

5. G=(V,E)

7. Undirected
Directed
Bi-directed
Mixed
Cyclical
Acyclical
Multigraph
Simple graph
Complete graph

8. Why graphs

9. Internet and
networks
Human
relationships
Staging Human body

10. It’s a
graph!

11. Graphs are fun

12. Graphs are easy to work with

13. DEMO
neo4j org structure

14. Graphs are whiteboard
friendly

15. Graphs
algorithms/performance

17. Loading data
NEO4J STORED PROCEDURE

22. LOADING DATA
BACKGROUND TASK EXECUTOR

23. Liferay neo4j
driver

26. Who does Jorge
manage?

30. Who ARE THE
CONTENT CREATORS?

32. Who hasn’t created
any content?

35. Who to follow?

37. How far are they are
from me?

39. × Discovering relationships,
behavior, interests
× Providing suggestions on products

40. staging?
Again?

41. 1.
Advanced publication tool
Content can be assembled and
reviewed on a staging site and can
be published to live

42. A staging publication process
replicates data between sites and
performs extra operations – such as
validation
2.
replication

43. Image
Web
Content
Blogs

44. Entity
Staging is operating on a graph of
entities, discovering and processing
the relationships between them

45. wysiwyg behavior
In order to ensure a
smooth experience we
might need to pull
other contents too
reference validation
Certain business rules
needs to be validated
and reported back

46. no graph stored
There is no
information before
the execution of the
graph
graph maintenance
On edit approach vs
processing every time
XML format
Performance
considerations –
especially on the
memory side

47. graph not homogenous
The graph vertices are not the
same – graph operations not
possible
static calling
Pre-defined entry points
combined with a static
controlling setup

48. Image
Content
Blog
Image
2
Folder
Content
2

49. Science kicks in – Enter
graph theory

50. Topological
sorting– coffman
graham

51. Image
Content
Blog
Image
2
Folder
Content
2

52. Image
Content Blog
Image
2
Folder
Content
2

53. Image
2
ContentBlog
Image Folder
Content
2

54. Directed
Direction is important to tell
what comes after what –
This is defined in the business logic
Graph
Duh!
Acyclical
In a cycle everything
has a predecessor and a
successor

58. Clean
bathroom
Sweep floors Wash windows
Armond $2 $3 $3
Francine $3 $2 $3
Herbert $3 $3 $2
Armond – Clean bathroom
Francine – Sweep floors
Herbert – Wash windows

59. Name/Task Writing a unit
test
Implement a
new staging
data handler
Fix a bug in a
BackgroundTas
kExecutor
Mária f(x) f(x) f(x)
Dániel f(x) f(x) f(x)
Ákos f(x) f(x) f(x)

60. Graph creation

62. Graph searching

63. × Path finding
× Artifical intelligence

64. × Not using Neo4j
× JGraphT library

65. × Finding insurance fraudulant
activity
× Risk assessement

66. × News site – content with links
to other content
× Panama papers

67. Structural
analysis

68. × Parkinson’s disease
× Protein struture prediction
× Cancer research

69. László babai
university of chicago
graph isomorphism can be solved in quasi
polinomial time

70. × Static code analysis – Codecheck,
Liferay Source Formatter
× Abstract Syntax Tree (AST)
× Abstract Semantic Graph (ASG)

71. Predicting the
future

72. × Probability distribution over graphs
× Complex network modeling
× Erdos-Rényi model

73. Pál
erdos

74. × Statistics gathering in a graph
form and analysing the
produced result

75. It’s a
graph!

76. Questions?

77. Gists
@matethurzo